Seeing Eye-to-Eye: Do Intergroup Biases Operate Similarly for Younger and Older Adults?
Bibliographic record
Abstract
Because of their relatively temporary group memberships, age groups represent an intriguing test of theories of intergroup relations. In spite of this unique feature, virtually no research has examined age group relations from an intergroup perspective. The present study investigated the role of two influential intergroup factors, degree of group identification and threats to group status, in younger and older adults' evaluations of their ingroup (own age group) and the outgroup (other age group). Participants were placed in situations in which their ingroup was either superior or inferior to the outgroup. Several measures of bias were then assessed, including ingroup favoritism, perceived similarity, social distance, outgroup homogeneity, and self-stereotyping. The results support the notion that age groups are unique from other groups, as age influenced all forms of bias. In particular, young adults exhibited more biases than older adults by perceiving less similarity and distancing themselves more from the outgroup. These findings suggest that older adults' greater familiarity with the outgroup might attenuate their age-based biases compared with younger participants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".